TY - GEN
T1 - An parallelized deep packet inspection design in software defined network
AU - Li, Yunchun
AU - Fu, Rong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/5/11
Y1 - 2014/5/11
N2 - Deep packet inspection (DPI) is a key technology in software defined network (SDN) which can centralize network policy control and accelerate packet transmission. In this paper, we propose a new SDN architecture with DPI module. Base on the centralization idea of SDN, we deploying a parallel DPI to the control layer. We present DPI interface in the SDN controller and discuss OpenFlow protocol extension. Paralleling the DPI algorithm effectively reduces the time of detecting packets and sending flow tables. We also describe an Adaptive Highest Random Weight with an additional feedback corresponding to queue length and string length matching at each processor. The original Highest Random Weight (HRW) hash ensures the connection locality. Treating all tasks as the same weight just balances the workload over the number of different task. By adding the adjustment multiplier and combined with the characteristics of the fixed hash function, the system can allocate resource dynamically and achieve connection-level parallelism in consideration of the processing time for per packet.
AB - Deep packet inspection (DPI) is a key technology in software defined network (SDN) which can centralize network policy control and accelerate packet transmission. In this paper, we propose a new SDN architecture with DPI module. Base on the centralization idea of SDN, we deploying a parallel DPI to the control layer. We present DPI interface in the SDN controller and discuss OpenFlow protocol extension. Paralleling the DPI algorithm effectively reduces the time of detecting packets and sending flow tables. We also describe an Adaptive Highest Random Weight with an additional feedback corresponding to queue length and string length matching at each processor. The original Highest Random Weight (HRW) hash ensures the connection locality. Treating all tasks as the same weight just balances the workload over the number of different task. By adding the adjustment multiplier and combined with the characteristics of the fixed hash function, the system can allocate resource dynamically and achieve connection-level parallelism in consideration of the processing time for per packet.
KW - Adaptive Highest Random Weight
KW - Deep Packet Inspection
KW - SDN Controller
KW - Software Defined Network
UR - https://www.scopus.com/pages/publications/84949928980
U2 - 10.1109/ICITEC.2014.7105560
DO - 10.1109/ICITEC.2014.7105560
M3 - 会议稿件
AN - SCOPUS:84949928980
T3 - Proceedings of 2nd International Conference on Information Technology and Electronic Commerce, ICITEC 2014
SP - 6
EP - 10
BT - Proceedings of 2nd International Conference on Information Technology and Electronic Commerce, ICITEC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Information Technology and Electronic Commerce, ICITEC 2014
Y2 - 20 December 2014 through 21 December 2014
ER -